The economy is something that is rapidly evolving and is hard to keep track of. In order to understand how the economy is constantly changing, we chose to focus our question on how global development affects certain factors, such as student populations, employment rates, and CO2 emissions. The dataset we used to answer our questions was data published by World Bank, and it will allow us to gain a better understanding of how economic development affects said factors.
Our dataset provides many interesting observations based on the variables it contains. Out of the 35 in our dataset, the country that produced the most CO2 emissions was Trinidad and Tobago. Regarding employment rate, Solomon Islands had the highest female employment rate of all the countries, while had the highest male employment rate. Additionally, United States had the highest average income out of all the countries. As for education, India had the most primary and secondary students enrolled over the course of 29 years.
While the raw dataset contains lots of specific information, it is hard to sift through its many columns. Below is a table that has been made to be more digestible to the reader by combining certain columns of data together.
| Country | Average Income (Current USD) | Average Population | Average Primary Students | Average Secondary Students | Average Female Employment (Employment:Population (female age 15+)) | Average Male Employment (Employment:Population (male age 15+)) | Average CO2 Emissions (Metric tons per capita) |
|---|---|---|---|---|---|---|---|
| United States | 35443.5934 | 292988563.2 | 24866699.09 | 24535708.67 | 54.25976 | 67.49162 | 18.7668335 |
| United Kingdom | 29695.8097 | 81783471.9 | 3336440.19 | 7863858.42 | 51.45686 | 64.48755 | 8.6745047 |
| Germany | 29173.8251 | 145312593.3 | 6300313.32 | 12202867.00 | 47.35521 | 62.75255 | 10.0077367 |
| Australia | 27952.0207 | 25847180.1 | 3395859.38 | 2008642.23 | 52.86183 | 67.55841 | 16.7741632 |
| France | 27597.0211 | 62862997.6 | 4064026.26 | 5898663.70 | 44.07145 | 56.65345 | 5.8157344 |
| Canada | 27452.9253 | 105758229.8 | 14650170.93 | 10134869.74 | 55.53365 | 65.97228 | 16.2550293 |
| New Zealand | 20587.8960 | 6534456.9 | 593517.89 | 174507.00 | 55.67872 | 69.67538 | 7.8525738 |
| Trinidad and Tobago | 8162.0421 | 1301275.7 | 162431.84 | 100239.00 | 47.06403 | 72.39417 | 24.4207556 |
| Argentina | 7299.0900 | 41971420.8 | 4879024.19 | 4115215.44 | 42.73017 | 67.10479 | 4.0506289 |
| Mexico | 6071.7346 | 60987038.5 | 4566309.41 | 5370440.66 | 38.83862 | 78.45200 | 4.0855966 |
| Venezuela, RB | 5939.6200 | 27437690.5 | 3925834.64 | 2379958.96 | 42.82741 | 71.37169 | 6.3489434 |
| Turkey | 5775.8120 | 67704438.5 | 6388259.08 | 7021971.20 | 25.82472 | 66.18303 | 3.5030672 |
| Brazil | 5519.6699 | 7350192.8 | 1141636.08 | 555996.46 | 45.45441 | 72.44914 | 1.8877168 |
| Russian Federation | 5212.6710 | 470543.4 | 79373.95 | 21009.14 | 51.16797 | 64.67103 | 11.4839522 |
| South Africa | 3889.7243 | 47799352.2 | 7450077.67 | 4543342.90 | 30.78914 | 48.98600 | 8.7958784 |
| Dominican Republic | 3575.4839 | 9003738.7 | 1256906.33 | 805466.45 | 38.15617 | 73.98917 | 2.0863641 |
| Cuba | 3456.1048 | 11136884.9 | 903673.25 | 830083.63 | 36.78993 | 65.28155 | 2.6214347 |
| Colombia | 3335.7609 | 183216830.0 | 18245755.17 | 24094869.07 | 46.31145 | 74.80890 | 1.6071200 |
| Jamaica | 3314.5712 | 2713364.4 | 300872.38 | 236080.05 | 48.01721 | 67.36359 | 3.4378203 |
| Peru | 2943.4224 | 38714254.8 | 4919608.25 | 3794783.71 | 59.30286 | 78.51107 | 1.2984604 |
| Fiji | 2937.2080 | 4106439.3 | 350967.30 | 467328.49 | 37.05510 | 75.53779 | 1.1662469 |
| China | 2317.4949 | 1289438392.9 | 112416740.68 | 82276024.64 | 65.05903 | 77.06503 | 4.2575076 |
| Guatemala | 1980.9712 | 32274739.8 | 2318994.35 | 2568202.95 | 39.18890 | 83.42683 | 0.8028696 |
| Egypt, Arab Rep. | 1567.2990 | 75884896.9 | 9185029.68 | 7402791.82 | 16.51566 | 67.92445 | 2.0032967 |
| Indonesia | 1399.7777 | 225523340.9 | 29538986.79 | 17236218.07 | 46.71521 | 78.84424 | 1.5060257 |
| Honduras | 1283.9467 | 13097557.3 | 2083115.22 | 775975.96 | 42.48355 | 83.15465 | 0.8533423 |
| Nigeria | 1115.3110 | 140709456.6 | 20149234.26 | 7699497.65 | 51.22269 | 60.73607 | 0.5454091 |
| Papua New Guinea | 983.3821 | 20615710.9 | 1933546.00 | 2360635.62 | 57.69959 | 58.97852 | 0.5860981 |
| Solomon Islands | 885.3929 | 822878.6 | 111972.18 | 97326.80 | 80.91783 | 83.78607 | 0.3757343 |
| Pakistan | 741.7573 | 159446862.0 | 17951283.26 | 9297347.67 | 18.04345 | 81.03621 | 0.7907704 |
| India | 741.1684 | 1132564205.9 | 123750290.96 | 94937446.28 | 26.01486 | 76.89052 | 1.1015140 |
| Bangladesh | 608.5477 | 135813155.0 | 16630850.62 | 11708118.25 | 27.41669 | 82.11459 | 0.2806398 |
| Haiti | 514.4021 | 9137952.5 | 1203846.43 | NaN | 51.04866 | 64.92435 | 0.1847010 |
| Ethiopia | 213.7654 | 76844164.2 | 8298188.42 | 2349818.14 | 69.18817 | 87.06334 | 0.0680738 |
| Congo, Dem. Rep. | 205.6671 | 56420915.2 | 8313774.59 | 2975326.69 | 65.16507 | 67.42121 | 0.0390857 |
Our table shows that the average income of a country does not seem to be related to the average population. However, our table does show that average CO2 emission rates increase in relation to average income.
This stacked bar chart depicts the percentage of the population in a primary and secondary school based on the country.
This chart shows that many people do not attend secondary school after primary school.
This scatterplot depicts how the employment to population ratio per country affects CO2 emissions.
This chart shows that CO2 emissions peaks when a country has around 60-65% employment to population ratio.
This diverging bar chart depicts a country’s CO2 emission growth rates.
This chart shows that most countries’ CO2 emissions are increasing over time.